Dan Lu Senior Staff Scientist Contact LUD1@ORNL.GOV All Publications GenAI4UQ: A software for forward and inverse uncertainty quantification using conditional generative AI Recommendations for Comprehensive and Independent Evaluation of Machine Learning-Based Earth System Models An Alternative Ensemble Streamflow Prediction Approach Using Improved Subseasonal Precipitation Forecasts from the North America Multi-Model Ensemble Phase II A novel conditional generative model for efficient ensemble forecasts of state variables in large-scale geological carbon storage Machine learning opportunities for nucleosynthesis studies Distance preserving machine learning for uncertainty aware accelerator capacitance predictions ExoTST: Exogenous-Aware Temporal Sequence Transformer for Time Series Prediction Temporal sequence transformer to advance long-term streamflow prediction ORBIT: Oak Ridge Base Foundation Model for Earth System Predictability... Probabilistic neural networks for improved analyses with phenomenological R-matrix A Scalable Real-Time Data Assimilation Framework for Predicting Turbulent Atmosphere Dynamics Improving streamflow predictions across CONUS by integrating advanced machine learning models and diverse data FutureTST: When Transformers Meet Future Exogenous Drivers Comparison of machine learning and electrical resistivity arrays to inverse modeling for locating and characterizing subsurface targets A Diffusion-Based Uncertainty Quantification Method to Advance E3SM Land Model Calibration Oak Ridge National Laboratory's Strategic Research and Development Insights for Digital Twins Advancing earth system model calibration: a diffusion-based method Improving Streamflow predictions with vision transformers... Improving the estimation of atmospheric water vapor pressure using interpretable long short-term memory networks Advancing spatiotemporal forecasts of CO 2 plume migration using deep learning networks with transfer learning and interpretation analysis Explainable machine learning model for multi-step forecasting of reservoir inflow with uncertainty quantification Accelerating Scientific Simulations with Bi-Fidelity Weighted Transfer Learning Advancing subseasonal reservoir inflow forecasts using an explainable machine learning method... Multi-module-based CVAE to predict HVCM faults in the SNS accelerator Uncertainty quantification of the convolutional neural networks on permeability estimation from micro-CT scanned sandstone and carbonate rock images Pagination Current page 1 Page 2 Page 3 … Next page ›› Last page Last » Key Links Curriculum Vitae Google Scholar ORCID GitHub Organizations Computing and Computational Sciences Directorate Computational Sciences and Engineering Division Advanced Computing Methods for Physical Sciences Section Computational Earth Sciences Group
